Energy Efficient Clustering Techniques for Mobile Data Gathering in Distributed Wsn

Now a days the “big data” emerged as a hot topic because of the tremendous growth of the Information and Communication Technology (ICT). The key contributors of the big data in the networks is the distributed Wireless Sensor Networks (WSNs). The data generated by an individual sensor node may not appear to be significant, the overall data generated across numerous sensors in the densely distributed WSNs can produce a significant portion of the big data. The researchers introduces a data-gathering technologies for large-scale wireless sensor networks by introducing mobility into the network. An M-collector (mobile data collector) starts the data-gathering tour periodically from the static data sink, polls each sensor while traversing its transmission range, then directly collects data from the sensor in single-hop communications, and finally transports the data to the static sink. We mainly focus on the problem of minimizing the length of each datagathering tour and refer to this as the single-hop data-gathering problem (SHDGP). We have a data-gathering algorithm where multiple M-collectors traverse through several shorter sub tours concurrently to satisfy the distance/time constraints. Simulation results will try to demonstrate that the proposed data-gathering algorithm can greatly shorten the moving distance of the collectors and significantly prolong the network lifetime.